Detecting sound by employing laser speckle interferometry is known in the art. To that end a laser beam is projected toward the sound source or on to a surface acoustically coupled with the sound source (i.e., a surface which vibrates according to the sound produced by the sound source). The laser beam impinges on the surface and diffusively reflects therefrom. The diffusive reflection of different portions of the light beam results in a random shift of the phases of the portions of the corresponding light waves and a random distribution of the intensities thereof. Consequently, the waves corresponding to the diffusively reflected portions of the beam interfere with each other. This results in a light distribution with varying intensity. These random variations in the intensity create a speckle pattern for each light beam. The speckle pattern varies with the vibrations of the surface. An imager acquires an image of the reflection of the laser beam from the surface. These images of the reflection of the laser beam include speckle patterns. The shift of the speckle patterns between subsequent images is related to the vibrations of the surface and thus to the sound produced by the sound source.
Reference is now made to FIG. 1, which is a schematic illustration of a system, generally referenced 10, for determining the vibrations of an object, which is known in the art. System 10 includes an imager 12. Imager 12 includes an imaging sensor 14 and a lens 16. Lens 16 is optically coupled with imaging sensor 14. A beam of coherent light 18 (e.g., a laser light) impinges on the surface of an object 20 and diffusively reflects therefrom. As mentioned above, this diffusive reflection results in a speckle pattern. Imager 12 acquires the speckle patterns in a defocused image plane 22. This defocused image plane is located at a distance Z from the object. The angular displacement of the object results in a shift, ΔH, of the speckle pattern in defocused image plane 22 and thus of the speckle pattern in the acquired image.
The publication to Zalevsky et al. entitled “Simultaneous Remote Extraction of Multiple Speech Sources and Heart Beats from Secondary Speckles Pattern” directs to a system for extraction of remote sounds. In the system directed to by Zalevsky, a laser beam is directed toward an object and employs a defocused image and detects temporal intensity fluctuations of the imaged speckles pattern and their trajectory. From the trajectories of the speckles pattern the system directed to by Zalevsky detects speech sounds and heartbeat sounds.
U.S. Pat. No. 8,286,493 to Bakish, entitled “Sound Source Separation and Monitoring Using Direction Coherent Electromagnetic Waves” directs to a system and methods in which a plurality of laser beams are pointed toward multiple sound sources. The reflection of each of the beams is related to a corresponding sound source. The speckle pattern resulting from the reflection of each beam is analyzed to determine the sound produced by the corresponding source. Thus, source separation may be achieved.
The publication to Chen et al., entitled “Audio Signal Reconstructions Based on Adaptively Selected Seed Points from Laser Speckle Images” directs to a method for estimating the vibrations of an object according to variations in the gray level values of selected pixels, also referred to as seed points, in a defocused image of the speckle pattern. To that end, the method directed to Chen acquires a plurality of images and determines a linear correspondence between the variations in the gray level values of the seed points and the vibration of the object by estimating the parameters that minimize the difference between the vibration of the object at two different seed points, across all images (i.e., since the difference between the equations are used the vibration is not a parameter in the optimization). The vibration between images is determined as the weighted sum of the vibration due to each seed point.
The publication entitled “Breath Sound Distribution of Patient With Pneumonia and Pleural Effusion” to Mor et al., describes the experimental results of a system for detecting a breath sound distribution map. The system directed to by Mor includes 40 contact sound sensors, assembled on two planar arrays, which cover the posterior lung area. The sensors are attached to the patient's back by low-suction vacuum controlled by a computer. The sounds captured by the sensors are filtered to the desired frequency range of breath (between 150-250 Hertz). The signals are processed and the breath sound distribution is displayed as a grayscale image. Areas with high lung vibration energy appear black and areas with low lung vibration energy appear light grey. A physician identifies whether the patient is suffering from Pneumonia or Pleural Effusion based on these images.
PCT Application Publication 2002/036015 to Tearney et al directs to employing focused images of laser speckles for measuring microscopic motion (e.g., resulting from blood flow), such as Brownian motion of tissue in vivo, to gather information about the tissue. According to D1, coherent or partially coherent light is reflected from the tissue to form a speckle pattern at a detector. Due to motion of reflectors within the tissue, the speckle pattern changes over time. In operation, coherent light, such as laser light is transmitted through optical fiber toward a tissue sample (e.g., static tissue, moving tissue, atherosclerotic plaque and the like). The device can be placed directly in contact with the sample or a short distance therefrom. The light enters the sample, where it is reflected by molecules, cellular debris or microstructures (such as organelles, microtubules), proteins, cholesterol crystals. The light remitted from the sample is focused on the distal end of a fibers array (fibroscope). The focused light travels through the fibers to a CCD detector. Due to interference, a speckle pattern forms at the CCD detector. The resulting speckle pattern is analyzed. According to Tearney, a reference image is acquired and correlated with successive images. Since the speckle pattern is each successive image is different the correlation between the acquired image and the reference image decreases. According to Tearney, various physiological conditions can be determined from the de-correlation time constant. It is noted that Tearney does not measure the motion that cause the change in the speckle pattern just the result of such a motion. Furthermore, Tearney directs to illuminating multiple locations of the tissue in succession, forming a separate series of speckle patterns for each respective location, and then analyzing each separate series of speckle patterns and comparing the separate series to deduce structural and/or biomechanical differences between the respective locations of the tissue.